Topsis Analysis
Project description
Topsis Analysis
Installation
Use the package manager pip to install topsis.
pip install topsis-neeraj
Usage
Following query on terminal will provide you the topsis analysis for input csv file.
topsis -n "dataset-name" -w "w1,w2,w3,w4,..." -i "i1,i2,i3,i4,..."
Do not mention the file format, 'csv', as part of dataset-name. w1,w2,w3,w4 represent weights, and i1,i2,i3,i4 represent impacts where 1 is used for maximize and 0 for minimize. Size of w and i is equal to number of features.
Note that the first row and first column of dataset is dropped
Rank 1 signifies best decision
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate.
License
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
| Filename, size | File type | Python version | Upload date | Hashes |
|---|---|---|---|---|
| Filename, size topsis_neeraj-0.0.1-py3-none-any.whl (4.0 kB) | File type Wheel | Python version py3 | Upload date | Hashes View |
| Filename, size topsis-neeraj-0.0.1.tar.gz (2.7 kB) | File type Source | Python version None | Upload date | Hashes View |
Close
Hashes for topsis_neeraj-0.0.1-py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | bbde137185b5c324c51adabb6edab8f63fe5606a52e9b69da4487bb657dc70dc |
|
| MD5 | a711e9a6b37db48be3a1b04ba91c0488 |
|
| BLAKE2-256 | fcd61acc566cdb73356695dcd99868498c086caa0939e0b4936b777de0c917a4 |
